CD44ICD promotes breast cancer stemness via PFKFB4-mediated glucose metabolism.

CD44 is a single-pass cell surface glycoprotein that is distinguished as the first molecule used to identify cancer stem cells in solid tumors based on its expression. In this regard, the CD44high cell population demonstrates not only the ability to regenerate a heterogeneous tumor, but also the ability to self-regenerate when transplanted into immune-deficient mice. However, the exact role of CD44 in cancer stem cells remains unclear in part because CD44 exists in various isoforms due to alternative splicing. Methods: Gain- and loss-of-function methods in different models were used to investigate the effects of CD44 on breast cancer stemness. Cancer stemness was analyzed by detecting SOX2, OCT4 and NANOG expression, ALDH activity, side population (SP) and sphere formation. Glucose consumption, lactate secretion and reactive oxygen species (ROS) levels were detected to assess glycolysis. Western blot, immunohistochemical staining, ELISA and TCGA dataset analysis were performed to determine the association of CD44ICD and PFKFB4 with clinical cases. A PFKFB4 inhibitor, 5MPN, was used in a xenograft model to inhibit breast cancer development. Results: In this report, we found that the shortest CD44 isoform (CD44s) inhibits breast cancer stemness, whereas the cleaved product of CD44 (CD44ICD) promotes breast cancer stemness. Furthermore, CD44ICD interacts with CREB and binds to the promoter region of PFKFB4, thereby regulating PFKFB4 transcription and expression. The resultant PFKFB4 expression facilitates the glycolysis pathway (vis-à-vis oxidative phosphorylation) and promotes stemness of breast cancer. In addition, we found that CD44ICD and PFKFB4 expressions are generally up-regulated in the tumor portion of breast cancer patient samples. Most importantly, we found that 5MPN (a selective inhibitor of PFKFB4) suppresses CD44ICD-induced tumor development. Conclusion: CD44ICD promotes breast cancer stemness via PFKFB4-mediated glycolysis, and therapies that target PFKFB4 (e.g., 5MPN therapy) may lead to improved outcomes for cancer patients

Palladium Cobalt-nickel mixed oxides Surface modification Synergistic interaction Lean methane combustion

The effective transformation of lignin is an essential part of realizing the comprehensive utilization of biomass. In this study, a one-pot method for the depolymerization of corn stover lignin used aluminum phosphate (NiAPO-5) zeolite catalyst contained Brønsted acid, Lewis acid and hydrogenation sites was proposed. It was found that the number of Brønsted acid sites was increased after NiAPO-5 was reduced with H2. The yield of monomers and residue were 35.70% and 38.09% at 235 ◦C for 3 h, respectively. The result of 2D HSQC NMR showed that the NiAPO-5 (H2) catalyst significantly affected the cleavage of β-O-4 bonds. The distribution of products and the stability of catalyst revealed that NiAPO-5 (H2) was an efficient catalyst for the depolymerization of lignin

Chemically induced Jahn–Teller ordering on manganite surfaces

Physical and electrochemical phenomena at the surfaces of transition metal oxides and their coupling to local functionality remains one of the enigmas of condensed matter physics. Understanding the emergent physical phenomena at surfaces requires the capability to probe the local composition, map order parameter fields and establish their coupling to electronic properties. Here we demonstrate that measuring the sub-30-pm displacements of atoms from high-symmetry positions in the atomically resolved scanning tunnelling microscopy allows the physical order parameter fields to be visualized in real space on the single-atom level. Here, this local crystallographic analysis is applied to the in-situ-grown manganite surfaces. In particular, using direct bond-angle mapping we report direct observation of structural domains on manganite surfaces, and trace their origin to surface-chemistryinduced stabilization of ordered Jahn–Teller displacements. Density functional calculations provide insight into the intriguing interplay between the various degrees of freedom now resolved on the atomic level

Infrared Imaging of Magnetic Octupole Domains in Non-collinear Antiferromagnets

Magnetic structure plays a pivotal role in the functionality of antiferromagnets (AFMs), which not only can be employed to encode digital data but also yields novel phenomena. Despite its growing significance, visualizing the antiferromagnetic domain structure remains a challenge, particularly for non-collinear AFMs. Currently, the observation of magnetic domains in non-collinear antiferromagnetic materials is feasible only in Mn$_{3}$Sn, underscoring the limitations of existing techniques that necessitate distinct methods for in-plane and out-of-plane magnetic domain imaging. In this study, we present a versatile method for imaging the antiferromagnetic domain structure in a series of non-collinear antiferromagnetic materials by utilizing the anomalous Ettingshausen effect (AEE), which resolves both the magnetic octupole moments parallel and perpendicular to the sample surface. Temperature modulation due to the AEE originating from different magnetic domains is measured by the lock-in thermography, revealing distinct behaviors of octupole domains in different antiferromagnets. This work delivers an efficient technique for the visualization of magnetic domains in non-collinear AFMs, which enables comprehensive study of the magnetization process at the microscopic level and paves the way for potential advancements in applications.Comment: National Science Review in pres

Prognostic values of ALDOB expression and 18F-FDG PET/CT in hepatocellular carcinoma

PurposeThe glycolytic enzyme fructose 1,6-bisphosphate aldolase B (ALDOB) is aberrantly expressed and impacts the prognosis in hepatocellular carcinoma (HCC). Hepatic ALDOB loss leads to paradoxical upregulation of glucose metabolism, favoring hepatocellular carcinogenesis. Nevertheless, the relationship between ALDOB expression and 18F-fluorodeoxyglucose (18F-FDG) uptake, and their effects on HCC prognosis remain unclear. We evaluated whether ALDOB expression is associated with 18F-FDG uptake and their impacts on HCC prognosis prediction.MethodsChanges in ALDOB expression levels and the prognostic values in HCC were analyzed using data from The Cancer Genome Atlas (TCGA) database. Ultimately, 34 patients with HCC who underwent 18F-FDG positron emission tomography/computed tomography (PET/CT) preoperatively were enrolled in this retrospective study. ALDOB expression was determined using immunohistochemistry (IHC) staining, and the maximum standardized uptake value (SUVmax) of HCC was calculated from the 18F-FDG PET/CT scans. The relationship between ALDOB expression and SUVmax was examined, and their impacts on overall survival were evaluated using Cox proportional hazards models and Kaplan–Meier survival analysis. ALDOB overexpression in HUH7 and 7721 cells was used to analyze its role in tumor metabolism.ResultsAccording to TCGA database, the ALDOB mRNA level was downregulated in HCC compared to normal tissue, and significantly shortened overall survival in HCC patients. ALDOB protein expression was similarly decreased in IHC findings in HCC than that in adjacent normal tissues (P<0.05) and was significantly associated with tumor size (P<0.001), high tumor-node-metastasis stage (P=0.022), and elevated SUVmax (P=0.009). ALDOB expression in HCC was inversely correlated with SUVmax (r=-0.454; P=0.012), and the optimal SUVmax cutoff value for predicting its expression was 4.15. Prognostically, low ALDOB expression or SUVmax ≥3.9 indicated shorter overall survival time in HCC. Moreover, COX regression analysis suggested high SUVmax as an independent prognostic risk factor for HCC (P=0.036). HCC patients with negative ALDOB expression and positive SUVmax (≥3.9) were correlated with worse prognosis. ALDOB overexpression in HCC cells significantly decreases 18F-FDG uptake and lactate production.ConclusionSUVmax in HCC patients is inversely correlated with ALDOB expression, and 18F-FDG PET/CT may be useful for ALDOB status prediction. The combined use of ALDOB expression and 18F-FDG PET/CT data can provide additional information on disease prognosis in HCC patients

PFKFB4 Promotes Breast Cancer Metastasis via Induction of Hyaluronan Production in a p38-Dependent Manner

Background/Aims: The bi-functional enzyme 6-phosphofructo-2-kinase/fructose-2, 6-biphosphatase-4 (PFKFB4) is highly expressed in many types of cancer and its requirement for tumor survival has been demonstrated in glioma, lung, and prostate cancers. However, whether PFKFB4 plays a role in the tumor metastasis remains uncertain. This study explores the role of PFKFB4 in tumor metastasis and its underlying mechanisms in breast cancer cells. Methods: The expression of PFKFB4 was first analyzed using the Cancer Genome Atlas (TCGA) dataset, and confirmed by immunohistochemical staining of tissue microarray and breast cancer tissues from patient samples. Gain- and loss-of- function approaches were used to investigate the effects of PFKFB4 on breast cancer cell migration in vitro. Orthotopic xenograft model and experimental metastasis model were used to assess the effects of PFKFB4 on breast cancer cell metastasis in vivo. ELISA and immunofluorescence staining were used to examine HA production. Quantitative RT-PCR and western blotting were used to explore the mRNA and protein levels of HAS2, respectively. Results: We found that PFKFB4 enhances the migration/invasiveness of breast cancer cells in vitro as well as in vivo. Notably, the effects of PFKFB4 on migration are mediated by induction of HAS2 expression and HA production. Moreover, PFKFB4-induced HAS2 up-regulation depends upon the activation of p38 signaling. Conclusion: PFKFB4 promotes the metastasis of breast cancer cells via induction of HAS2 expression and HA production in a p38-dependent manner. Therefore, the PFKFB4/p38/HAS2 signaling pathway may serve as a potential therapeutic target for metastatic breast cancer

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Two ultraviolet radiation datasets that cover China

Ultraviolet (UV) radiation has significant effects on ecosystems, environments, and human health, as well as atmospheric processes and climate change. Two ultraviolet radiation datasets are described in this paper. One contains hourly observations of UV radiation measured at 40 Chinese Ecosystem Research Network stations from 2005 to 2015. CUV3 broadband radiometers were used to observe the UV radiation, with an accuracy of 5%, which meets the World Meteorology Organization's measurement standards. The extremum method was used to control the quality of the measured datasets. The other dataset contains daily cumulative UV radiation estimates that were calculated using an all-sky estimation model combined with a hybrid model. The reconstructed daily UV radiation data span from 1961 to 2014. The mean absolute bias error and root-mean-square error are smaller than 30% at most stations, and most of the mean bias error values are negative, which indicates underestimation of the UV radiation intensity. These datasets can improve our basic knowledge of the spatial and temporal variations in UV radiation. Additionally, these datasets can be used in studies of potential ozone formation and atmospheric oxidation, as well as simulations of ecological processes